TITLE:
Modeling the Dynamics of the Random Demand Inventory Management System
AUTHORS:
Jeremie Ndikumagenge, Jean Pierre Ntayagabiri
KEYWORDS:
Ergodic Markov Chain, Irreducible Markov Chain, Modeling, Optimization, Stochastic Processes
JOURNAL NAME:
Journal of Applied Mathematics and Physics,
Vol.11 No.2,
February
13,
2023
ABSTRACT: At any given time, a product stock manager is expected to carry out activities to check his or her holdings in general and to monitor the condition of the stock in particular. He should monitor the level or quantity available of a given product, of any item. On the basis of the observation made in relation to the movements of previous periods, he may decide to order or not a certain quantity of products. This paper discusses the applicability of discrete-time Markov chains in making relevant decisions for the management of a stock of COTRA-Honey products. A Markov chain model based on the transition matrix and equilibrium probabilities was developed to help managers predict the likely state of the stock in order to anticipate procurement decisions in the short, medium or long term. The objective of any manager is to ensure efficient management by limiting overstocking, minimising the risk of stock-outs as much as possible and maximising profits. The determined Markov chain model allows the manager to predict whether or not to order for the period following the current period, and if so, how much.